Comparative effectiveness of pathological techniques to improve lymph node yield from colorectal cancer specimens: a systematic review and network meta-analysis
HISTOPATHOLOGY(2022)
摘要
A number of randomised controlled trials (RCT) have compared different techniques to improve lymph node yield (LNY) in colorectal cancer specimens, but data on comparative effectiveness are sparse. Our aim was to compare the relative effectiveness and rank all available techniques. A systematic search of Embase, Cochrane, PubMed and Scopus was performed for randomised trials. Pairwise was meta-analysis performed if more than two homogeneous studies were available for each comparison. Network meta-analysis was used to rank and compare all available techniques. Fifteen studies fulfilled the inclusion criteria. Techniques that were compared included methylene blue (MB), glacial acetic acid, ethanol, distilled water and formaldehyde (GEWF), Carnoy solution (CS), patent blue (PB), formalin, fat clearing (FC) and their combinations. The overall quality of studies was found to be fair. In pairwise meta-analysis MB had a higher lymph node yield weighted mean difference (WMD) = 13.67 (4.83-22.51), P < 0.01, lower number of specimens with fewer than 12 lymph nodes log odds ratio = -1.88 (-2.8, -0.91), P < 0.01 and higher LNY in patients with prior chemoradiotherapy [WMD = 9.11 (3.15, 15.08), P = 0.02] compared to formalin. Evaluation of the network plot revealed a well-connected network. In network meta-analysis MBFC had a higher LNY with [mean difference (MD) 13 and 95% credible interval (CrI) = 2.09-23.91] compared to formalin. MBFC probability of being the best technique for LNY was 91.4%. In network meta-analysis MB did not have a statistically significant difference when compared to formalin. MBFCS seems to be the most effective technique for LNY. Further studies are required to make safe conclusions for outcomes such positive lymph nodes and upstaging.
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关键词
colorectal cancer, lymph node yield, network meta-analysis, pathology techniques
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